Biopharmaceutical supply chains represent a unique challenge for the timely manufacture of a reliable supply of biopharmaceutical medicines in a supply chain context. In section 1, I present an overview of the biopharmaceutical supply chain and discuss why a systemized approach to modeling the bioproduction process is important. Biopharmaceutical manufacturers need to maintain high service levels due to the life-saving nature of the drugs they produce. However long production lead times of 1-2 years and supply uncertainty due to production yields, quality issues, regulatory filings and technological change all necessitate a more detailed approach to understanding supply chain production and risk.

In Section 2, I present the Bioproduction Planning Problem in the context of regulatory restrictions. The model is structured to capture the constraints imposed by current and projected regulatory approvals of processes and facilities, and produce an optimal schedule that takes these restrictions into account. Empirical data is presented based on implementation at Bayer Healthcare's Berkeley, CA manufacturing site.

In section 3, I introduce a model for mitigating supply-side risk in supply chains with long lead times and non-independent (correlated) failure events. The model is motivated by the biopharmaceutical industry but applicable to a large set of supply chains. The model determines the minimum-cost safety stock required to provide a guaranteed minimum service level, in the presence of correlated manufacturing failures due to adverse events such as earthquakes or batch failures.

In section 4 I extend the model to look at a broader class of adverse events and supply chain configurations. Failure event types including partial batch failures and delayed release of batches from Quality Control and Assurance are modeled. I also examine scenarios with recourse, where the goal is to minimize the production cost of a finite number of additional batch starts rather than a fixed safety stock-based strategy.